Examination of Human Health Impacts Due to Adverse Climate Events Through the Use of Vulnerability Mapping: A Scoping Review.

Government officials, health professionals, and other decision makers are tasked with characterizing vulnerability and understanding how populations experience risks associated with exposure to climate-related hazards. Spatial analyses of vulnerable locations have given rise to climate change vulnerability mapping. While not a new concept, the spatial analyses of specific health outcomes remain limited. This review explores different methodologies and data that are used to assess vulnerability and map population health impacts to climate hazards. The review retrieved scholarly articles and governmental reports concerning vulnerability mapping of human health to the impacts of climate change in the United States, published in the last decade. After review, 37 studies were selected for inclusion. Climate-related exposures were distributed across four main categories, including: high ambient temperatures; flood hazards; vector-borne diseases; and wildfires. A number of different methodologies and measures were used to assess health vulnerability to climate-related hazards, including heat vulnerability indices and regression analyses. Vulnerability maps should exemplify how variables measuring the sensitivity and adaptive capacity of different populations help to determine the potential for climate-related hazards to have an effect on human health. Recommendations address methodologies, data gaps, and communication to assist researchers and stakeholders in directing adaptations to their most efficient and effective use.

Energy and material flows of megacities.

Understanding the drivers of energy and material flows of cities is important for addressing global environmental challenges. Accessing, sharing, and managing energy and material resources is particularly critical for megacities, which face enormous social stresses because of their sheer size and complexity. Here we quantify the energy and material flows through the world's 27 megacities with populations greater than 10 million people as of 2010. Collectively the resource flows through megacities are largely consistent with scaling laws established in the emerging science of cities. Correlations are established for electricity consumption, heating and industrial fuel use, ground transportation energy use, water consumption, waste generation, and steel production in terms of heating-degree-days, urban form, economic activity, and population growth. The results help identify megacities exhibiting high and low levels of consumption and those making efficient use of resources. The correlation between per capita electricity use and urbanized area per capita is shown to be a consequence of gross building floor area per capita, which is found to increase for lower-density cities. Many of the megacities are growing rapidly in population but are growing even faster in terms of gross domestic product (GDP) and energy use. In the decade from 2001-2011, electricity use and ground transportation fuel use in megacities grew at approximately half the rate of GDP growth.

Identifying individual risk factors and documenting the pattern of heat-related illness through analyses of hospitalization and patterns of household cooling.

BACKGROUND: As climate change increases the frequency and intensity of extreme heat events researchers and public health officials must work towards understanding the causes and outcomes of heat-related morbidity and mortality. While there have been many studies on both heat-related illness (HRI), there are fewer on heat-related morbidity than on heat-related mortality. OBJECTIVE: To identify individual and environmental risk factors for hospitalizations and document patterns of household cooling. METHODS: We performed a pooled cross-sectional analysis of secondary U.S. data, the Nationwide Inpatient Sample. Risk ratios were calculated from multivariable models to identify risk factors for hospitalizations. Hierarchical modeling was also employed to identify relationships between individual and hospital level predictors of hospitalizations. Patterns of air conditioning use were analyzed among the vulnerable populations identified. RESULTS: Hospitalizations due to HRI increased over the study period compared to all other hospitalizations. Populations at elevated risk for HRI hospitalization were blacks, males and all age groups above the age of 40. Those living in zip-codes in the lowest income quartile and the uninsured were also at an increased risk. Hospitalizations for HRI in rural and small urban clusters were elevated, compared to urban areas. CONCLUSIONS: Risk factors for HRI include age greater than 40, male gender and hospitalization in rural areas or small urban clusters. Our analysis also revealed an increasing pattern of HRI hospitalizations over time and decreased association between common comorbidities and heat illnesses which may be indicative of underreporting.

A top-down regional assessment of urban greenhouse gas emissions in Europe.

This paper provides an account of urban greenhouse gas (GHG) emissions from 40 countries in Europe and examines covariates of emissions levels. We use a "top-down" analysis of emissions as spatially reported in the Emission Dataset for Global Atmospheric Research supplemented by Carbon Monitoring for Action from 1153 European cities larger than 50 000 population in 2000 (comprising >81 % of the total European urban population). Urban areas are defined spatially and demographically by the Global Rural Urban Mapping Project. We compare these results with "bottom-up" carbon accounting method results for cities in the region. Our results suggest that direct (Scopes 1 and 2) GHG emissions from urban areas range between 44 and 54 % of total anthropogenic emissions for the region. While individual urban GHG footprints vary from bottom-up studies, both the mean differences and the regional energy-related GHG emission share support previous findings. Correlation analysis indicates that the urban GHG emissions in Europe are mainly influenced by population size, density, and income and not by biophysical conditions. We argue that these data and methods of analysis are best used at the regional or higher scales.